The thyroid hormone receptor (THR) is an important member of the nuclear receptor family. Activation of THR by environmental chemicals may cause the disruption of the endocrine system leading to adverse effects. We have developed Quantitative Structure-Activity Relationship (QSAR) models to facilitate the prioritization of putative endocrine disrupting chemicals (EDC) acting via THR for the experimental validation. We have assembled the largest database of binding affinities available at the time of this study for ligand binding domain (LBD) of THR�. Both continuous and classification QSAR models were developed with an external accuracy of R2=0.55 and CCR=0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinity of antagonists inhibiting the interaction of coactivator with AF-2 domain of THR� (R2=0.70). Furthermore, molecular docking studies were performed for THR� ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of AF-2 domain, supplemented by putative decoys/non-binders) using several THR� structures retrieved from the Protein Data Bank. We found that two agonist-bound THR� conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we conducted virtual screening of a chemical library screened by EPA as part of the Tox21 program to identify potential THR�-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to THR�. Models developed in this study can be employed to either identify environmental chemicals interacting with THR or, conversely, eliminate the THR-mediated mechanism of action for chemicals of concern.

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure based modeling methods

248th National Meeting (2014)

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